What AI Governance tools can’t do – limitations of AI Governance software

BI & Data Science Analyst at 10 Senses

The EU Artificial Intelligence Act (AI Act) is a European initiative to regulate Artificial Intelligence (AI). It aims to ensure that AI systems developed and deployed in the European Union are safe to use, follow fundamental values, and foster investment and innovation in the European AI market.

The topic of the AI Act and responsible AI is of utmost importance. As a result, we have already published a few articles in relation to these topics, like:


In the last article, we have proposed a few stellar Artificial Intelligence Governance tools that help businesses ensure responsible AI practices and be compliant with the rules imposed by the EU AI Act. Nevertheless, being aware of the possibilities of specific tools is as important as being aware of their limitations.

Although Artificial Intelligence (AI) Governance tools can effectively assist in fostering responsible use of AI within organizations and complying with AI regulation, they are not a remedy for all possible AI Governance issues you need to deal with.

Once you read this article, you will know:

  • Why is AI Governance important,
  • What is the AI Governance framework,
  • What can AI Governance tools help,
  • What can’t AI Governance tools do.


Why is AI Governance important?

Let’s start with a brief recap of the AI Governance basics.

It is the legal framework for Artificial Intelligence in the private and public sectors, ensuring that AI research and AI development follow ethical AI practices. Its objective is to close the gap between accountability and ethics in AI development.

The interest in AI Governance has been growing steadily over the past few years. Nevertheless, it has notably accelerated since 2021 due to the first initiatives concerning the EU AI Act. Truth be told, in 2022/2023, it even skyrocketed due to the introduction of machine learning large language models, such as ChatGPT or Bard.

What AI Governance tools cannot do - AI Governance search trend is growing

Based on Google trends data

AI Governance tries to define what impact AI technology has on human lives and who is to be held accountable for the actions of AI algorithms. As a result, it encompasses issues related to:

  • safety of AI systems,
  • legal and institutional structures for AI technology,
  • rules around access and control of personal data in AI systems,
  • moral and ethical questions about AI systems,
  • automation of AI in various industries and sectors.


Therefore, adopting the right AI Governance practices ensures that AI technology developed or deployed within organizations is safe, transparent, and compliant with legal requirements, such as the upcoming EU AI Act.

What is the AI Governance framework?

Basically, an AI Governance framework is a set of guidelines, processes, and technological tools that are used within organizations to ensure that the use of AI is aligned with the organizational rules, internal governance structures, legal requirements, and ethical standards.

Effective AI Governance practices shall be based upon core principles, such as:

  • transparency,
  • fairness,
  • data privacy,
  • data security,
  • accountability.


Since AI technologies raise such concerns, governing AI effectively can help companies achieve transparent and responsible AI practices. Moreover, taking into consideration the upcoming Artificial Intelligence Act, AI experts within organizations can proactively act upon AI Governance and ensure responsible AI practices and a risk management framework are in place.

AI Governance framework steps

Source: Navigating Muddy Waters: A Framework for Ethical AI Governance Inspired by the EU AI Act | by Raul Vizcarra Chirinos | LatinXinAI | Medium

Establishing the AI Governance needed to be compliant with the EU AI Act involves:

  • Assessment, including risk assessment by defining the purpose of AI systems, use cases, functionalities, measures to limit potential new risks, possibilities of reversing the outcomes of AI systems, or managing the risks of AI systems for society.
  • Creating an AI portfolio that unanimously detects high-risk AI systems and those AI systems that shall follow standard ethical guidelines and adhere to traditional codes of conduct (low-risk and minimal-risk systems).
  • Developing and testing AI systems, along with the requirements from the EU AI Act we outlined in our article here. In accordance with the responsible AI idea, high-risk systems shall establish certain procedures (technical documentation, traceability, data governance policies for training, testing models, etc.). On the other hand, low-risk systems only need to be aligned with transparency requirements.
  • Monitoring and maintaining AI Act compliance by ensuring transparency and clear understanding of AI solutions (clear documentation, instructions, functionalities description, performance measuring, outcomes validation).


It is also important that such governance frameworks have AI ethics, the company’s values, and an internal code of conduct as the backbone. It is also advisable that there be an internal AI Council that shall continuously monitor the use of AI and AI works or encourage AI innovation.

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How can AI Governance tools help?

AI Governance suites are powerful tools that can significantly help to govern AI effectively, meaning they establish and maintain effective AI Governance frameworks and be compliant with the EU AI Act.

In fact, AI Governance tools can help you with:

  • Continuous monitoring of AI systems in compliance with legal and privacy regulations, like, for example, the EU AI Act, to stay informed and up-to-date at any time,
  • Aligning AI practices within the company with ethical standards, such as fairness, transparency, data security, and privacy considerations,
  • Organization and managing massive amounts of data used by AI systems (for example, data quality and lineage tracking),
  • Monitoring the performance of AI models to ensure AI systems operate as intended,
  • Identifying when AI models need retraining or adjustments,
  • Identifying and mitigating risks associated with AI deployment, such as biases in the decision-making process, potential misuse, or negative consequences of AI technologies,
  • Providing detailed logs and records of AI system operations that is crucial for accountability and transparency,
  • Facilitating clear communications about AI initiatives, benefits, and risks,
  • Making AI decisions more interpretable and understandable to humans.


The above are just a few examples of the possibilities of AI governance tools. In fact, as AI technology advances and there is a possibility that AI regulations will become stronger in the future, such tools can become even more effective.

What can’t AI governance tools do?

When it comes to AI Governance tools limitations, such tools cannot:

  • Replacing human judgment,
  • Ensuring full accuracy,
  • Predicting all possible outcomes,
  • Ensuring complete privacy and security,
  • Automating all AI Governance tasks,
  • Working independently of human oversight,
  • Substituting for legal and regulatory compliance,
  • Fully resolving ethical challenges,
  • Making decisions on regulatory changes.


Replacing human judgment

Firstly, AI Governance tools cannot replace human judgments, especially in complex ethical, legal, and social situations. They can provide useful insights and recommendations, but the ultimate decision-making responsibility remains with humans or working groups within companies.

Ensuring full accuracy

Moreover, AI Governance platforms cannot ensure full accuracy. AI models, data, and algorithms are vulnerable to limitations and biases. The software can mitigate risk and potential biases but is not capable of completely eliminating them.

Predicting all possible outcomes

These days, AI technologies are applied and manipulated in unpredictable ways. They have enormous potential, and it is difficult for current AI data governance tools to foresee every possible scenario that may happen along with scaling AI or expanding AI reach due to international cooperation.

As a result, such software cannot predict all possible outcomes, misuse, and negative consequences of AI systems, especially in complex and dynamic environments.

Ensuring complete data privacy and security

AI Governance tools are effective in enhancing the privacy and security of AI systems. Nevertheless, they cannot ensure complete protection against all types of cyber threats and data breaches of sensitive information or privacy laws.

Such limitations are an offset of the ever-evolving nature of cyber threats and the inherent complexities of fully securing any technology system, especially those involving large-scale and diverse data sets, as is often the case with AI.

Automating all governance tasks

Although the establishment and maintenance of AI Governance fit perfectly for automation, there are certain areas within that cannot be easily automated.

These are aspects of AI Governance, such as:

  • data ethics,
  • establishing AI ethics and company values guidelines,
  • compliance with all the evolving AI regulations,
  • stakeholders engagement to be advocates and watchers of AI Governance within companies.


Such tasks usually require ongoing human involvement and internal cooperation.

Working independently of human oversight

What is more, AI governance tools require continuous monitoring and oversight by human experts. Only this way can they ensure that these systems function as intended and make necessary adjustments when they are necessary.

Substituting for legal and regulatory compliance

Such tools can help in checking, reaching, and monitoring compliance with the proposed legislation, like the Artificial Intelligence Act. Nevertheless, they cannot fully replace the need for organizations to understand the applicable laws and regulations.

It is advisable that organizations familiarize themselves with the regulatory framework and encourage ethical conduct towards AI technology development internally.

Fully resolving ethical challenges

Ethical challenges often involve subjective, context-dependent judgments and values that require human engagement. Ethical issues in AI, like fairness, data privacy, and the impact on employment, are multifaceted and can vary greatly across cultures and situations.

While AI governance tools can aid in mitigating certain ethical risks, the nuanced nature of ethical decision-making requires human involvement. They support ethical considerations but cannot make complex decisions that require a deep understanding of human rights and social norms.

Making decisions on regulatory changes

Finally, AI Governance tools can monitor and enforce compliance with existing regulations. Nevertheless, they may lack the capabilities to interpret or decide on changes to these regulations. Such decisions are typically the purview of legislative bodies, regulatory agencies, and human policymakers, who consider a wide range of societal, economic, and ethical implications before amending or introducing new ones.

As a result, they can serve as support systems, ensuring adherence to the rules set by humans, rather than being active participants in the legislative process and taking accountability.

Summing up, AI Governance platforms are powerful tools that can help you effectively establish and monitor responsible AI concepts within a company to ensure responsible and ethical AI and be compliant with regulatory requirements, like the EU Artificial Intelligence Act.

Nevertheless, they have certain limitations you should consider when deploying such software within your company, and remember that they cannot replace the need for careful, informed human oversight and decision-making.

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